A Multimodal Adaptive Wireless Control Interface for People With Upper-Body Disabilities

Abstract

This paper describes a multimodal body-machine interface (BoMI) to help individuals with upper-limb disabilities using advanced assistive technologies, such as robotic arms. The proposed system uses a wearable and wireless body sensor network (WBSN) supporting up to six sensor nodes to measure the natural upper-body gesture of the users and translate it into control commands. Natural gesture of the head and upper-body parts, as well as muscular activity, are measured using inertial measurement units (IMUs) and surface electromyography (sEMG) using custom-designed multimodal wireless sensor nodes. An IMU sensing node is attached to a headset worn by the user. It has a size of 2.9 cm 2.9 cm, a maximum power consumption of 31 mW, and provides angular precision of 1. Multimodal patch sensor nodes, including both IMU and sEMG sensing modalities are placed over the user able-body parts to measure the motion and muscular activity. These nodes have a size of 2.5 cm 4.0 cm and a maximum power consumption of 11 mW. The proposed BoMI runs on a Raspberry Pi. It can adapt to several types of users through different control scenarios using the head and shoulder motion, as well as muscular activity, and provides a power autonomy of up to 24 h. JACO, a 6-DoF assistive robotic arm, is used as a testbed to evaluate the performance of the proposed BoMI. Ten able-bodied subjects performed ADLs while operating the AT device, using the Test d'Évaluation des Membres Supérieurs de Personnes Âgées to evaluate and compare the proposed BoMI with the conventional joystick controller. It is shown that the users can perform all tasks with the proposed BoMI, almost as fast as with the joystick controller, with only 30% time overhead on average, while being potentially more accessible to the upper-body disabled who cannot use the conventional joystick controller. Tests show that control performance with the proposed BoMI improved by up to 17% on average, after three trials.

Sistema De Apoio Ao Turismo Acessível: Estudo E Conceptualização De Uma Aplicação Web

“…Também as aplicações móveis podem apresentar mecanismos proactivos e características colaborativas (Emrouzeh et al, 2017). Em suma, as TICs focam-se, não só na componente tecnológica de divulgação da informação, mas também em mecanismos que permitam assegurar a conexão com o mundo digital, nomeadamente tecnologias de assistência e/ou tecnologias adaptativas (Fall et al, 2018). Alguns exemplos práticos da aplicação das TICs no turismo acessível estão relacionados com a assistência na visita a museus como mostram o estudos de Angkananon et al, (2015), Haworth and Williams (2012) e Mesquita and Carneiro, (2016).…”

A Multichannel Wireless sEMG Sensor Endowing a <tex>$0.13 \ \mu \mathrm{m}$</tex> CMOS Mixed-Signal SoC

“…The body reference is generated with an on-chip LDO (VDD SoC /2 = 0.6-V), the potential of which can be applied to a dedicated electrode, or connected to the shared electrode. In the proposed sensor, the latter strategy is used to reduce the number of electrodes to a minimum (11 electrodes are required to record 10 sEMG channels, versus 21 for a classical differential recording system [5], [8], [11]).…”

“…When it comes to designing custom sEMG measurement tools, systemon-chip (SoC) bioamplifier circuits provide integrated multichannel solutions that may be the best currently available solution. For example, Intan Technologies amplifier chips such as the RHD2164 are suitable for highdensity sEMG (providing up to 64 recording channels), and the ADS129X chips from Texas Instrument provides up to 8 channels consuming 750 μW/Ch, for theoretical input referred noise (IRN) levels of 2.4 mV rms and 6 μ Vrms [7], [8].…”

“…We present a 10-channels wireless sEMG sensor that is based on a custom 0.13 μm CMOS mixed-signal SoC. Compared to existing systems, the proposed sensor is small [8]- [10], has a high channel count [6], [8]- [11], while having better or equivalent noise, power [7], [8], [11] and sampling rate [9] performances. Figure 1 shows the system-level concept of the proposed multichannel wireless sEMG sensor.…”

Design and Development of Portable LoRa-based Teleoperation Controller

“…By using an inertial measurement unit (IMU) sensor, a user can control a robotic arm more intuitively. (8)(9)(10) An IMU consists of two types of three-axis inertial sensors, i.e., accelerometers and gyroscopes, encapsulated in a polychlorinated biphenyl (PCB) semiconductor, which can be used to estimate the attitude of the device by estimating the relationship between the device direction and the gravity vector. (11) We used an MPU-6050 sensor with a three-axis accelerometer and a gyroscope to provide the input signal of the robotic-arm controller for teleoperation control.…”